INDEX

Explanations

proper nouns related to movies, books, or characters

oai_token-act-pair · gpt-3.5-turbo

occurrences of the suffix "er" in various contexts

oai_token-act-pair · gpt-4o-mini Triggered by @bot

New Auto-Interp

Top Features by Cosine Similarity

Comparing With GPT2-SMALL @ 1-res-jb

Configuration

jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.hook_resid_pre

Prompts (Dashboard)

24,576 prompts, 128 tokens each

Dataset (Dashboard)

Skylion007/openwebtext

Features

24,576

Data Type

torch.float32

Hook Point

blocks.1.hook_resid_pre

Architecture

standard

Context Size

128

Dataset

Skylion007/openwebtext

Hook Point Layer

Activation Function

relu

Embeds

PlotsExplanationShow Test FieldDefault Test Text

IFrame

Link

Not in Any Lists

No Comments

Negative Logits

ĸļ

-0.98

acebook

-0.68

itars

-0.66

ciating

-0.63

clud

-0.62

 Gazette

-0.58

rongh

-0.56

 Guinea

-0.56

chwitz

-0.56

 Mesa

-0.55

POSITIVE LOGITS

lich

0.94

rors

0.94

idge

0.90

inder

0.88

der

0.84

lein

0.83

rer

0.83

oll

0.82

idan

0.82

ger

0.81

Activations Density 0.037%

proper nouns related to movies, books, or characters

occurrences of the suffix "er" in various contexts

No Comments

No Known Activations